Identification of behaviour change techniques and engagement strategies to design a smartphone app to reduce alcohol consumption using a formal consensus method

Background: Digital interventions to reduce excessive alcohol consumption have the potential to have a broader reach and be more cost-effective than traditional brief interventions. However, there is not yet a strong evidence base on their ability to engage users or on their effectiveness. Objective: This study aimed to identify the behaviour change techniques (BCTs) and engagement strategies most worthy of further study by inclusion in a smartphone application (app) to reduce alcohol consumption, using formal expert consensus methods. Methods: The first phase of the study consisted of a Delphi exercise with three rounds. It was conducted with seven international experts in the field of alcohol and/or behaviour change. In the first round, experts identified BCTs most likely to be effective at reducing alcohol consumption and strategies most likely to engage users with an app; these were rated in the second round; and those rated as effective by at least four out of seven participants were ranked in the third round. The rankings were analysed using Kendall’s W coefficient of concordance, which indicates consensus between participants. The second phase consisted of a new, independent group of experts (n=43) ranking the BCTs that were identified in the first phase. The correlation between the rankings of the two groups was assessed using Spearman’s rank correlation coefficient. Results: Twelve BCTs were identified as likely to be effective. There was moderate agreement among the experts over their ranking (W=.465, χ2(11)=35.77, P<.001) and the BCTs receiving the highest mean rankings were self-monitoring, goal-setting, action planning, and feedback in relation to goals. There was a significant correlation between the ranking of the BCTs by the group of experts who identified them and a second independent group of experts (Spearman’s rho=.690, P=.01). Seventeen responses were generated for strategies likely to engage users. There was moderate agreement among experts on the ranking of these engagement strategies (W=.563, χ2(15)=59.16, P<.001) and those with the highest mean rankings were ease of use, design – aesthetic, feedback, function, design – ability to change design to suit own preferences, tailored information, and unique smartphone features. Conclusions: The BCTs with greatest potential to include in a smartphone app to reduce alcohol consumption were judged by experts to be self-monitoring, goal-setting, action planning, and feedback in relation to goals. The strategies most likely to engage users were ease of use, design, tailoring of design and information, and unique smartphone features

A Mobile App to Aid Smoking Cessation: Preliminary Evaluation of SmokeFree28

Background: Little is known about the effectiveness of mobile apps in aiding smoking cessation or their validity for automated collection of data on smoking cessation outcomes. Objective: We conducted a preliminary evaluation of SF28 (SF28 is the name of the app, short for SmokeFree28)—an app aimed at helping smokers to be smoke-free for 28 days. / Methods: Data on sociodemographic characteristics, smoking history, number of logins, and abstinence at each login were uploaded to a server from SF28 between August 2012 and August 2013. Users were included if they were aged 16 years or over, smoked cigarettes at the time of registration, had set a quit date, and used the app at least once on or after their quit date. Their characteristics were compared with data from a representative sample of smokers trying to stop smoking in England. The percentage of users recording 28 days of abstinence was compared with a value of 15% estimated for unaided quitting. Correlations were assessed between recorded abstinence for 28 days and well-established abstinence predictors. / Results: A total of 1170 users met the inclusion criteria. Compared with smokers trying to quit in England, they had higher consumption, and were younger, more likely to be female, and had a non-manual rather than manual occupation. In total, 18.9% (95% CI 16.7-21.1) were recorded as being abstinent from smoking for 28 days or longer. The mean number of logins was 8.5 (SD 9.0). The proportion recording abstinence for 28 days or longer was higher in users who were older, in a non-manual occupation, and in those using a smoking cessation medication. / Conclusions: The recorded 28-day abstinence rates from the mobile app, SF28, suggest that it may help some smokers to stop smoking. Further evaluation by means of a randomized trial appears to be warranted

Developing theory-informed interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework

Background: There is little systematic operational guidance about how best to develop complex interventions to reduce the gap between practice and evidence. This article is one in a series of articles documenting the development and use of the Theoretical Domains Framework (TDF) to advance the science of implementation research. Methods: The intervention was developed considering three main components: theory, evidence, and practical issues. We used a four-step approach, consisting of guiding questions, to direct the choice of the most appropriate components of an implementation intervention: Who needs to do what, differently? Using a theoretical framework, which barriers and enablers need to be addressed? Which intervention components (behaviour change techniques and mode(s) of delivery) could overcome the modifiable barriers and enhance the enablers? And how can behaviour change be measured and understood? Results: A complex implementation intervention was designed that aimed to improve acute low back pain management in primary care. We used the TDF to identify the barriers and enablers to the uptake of evidence into practice and to guide the choice of intervention components. These components were then combined into a cohesive intervention. The intervention was delivered via two facilitated interactive small group workshops. We also produced a DVD to distribute to all participants in the intervention group. We chose outcome measures in order to assess the mediating mechanisms of behaviour change. Conclusions: We have illustrated a four-step systematic method for developing an intervention designed to change clinical practice based on a theoretical framework. The method of development provides a systematic framework that could be used by others developing complex implementation interventions. While this framework should be iteratively adjusted and refined to suit other contexts and settings, we believe that the four-step process should be maintained as the primary framework to guide researchers through a comprehensive intervention development process

Statistical interaction modeling of bovine herd behaviors

While there has been interest in modeling the group behavior of herds or flocks, much of this work has focused on simulating their collective spatial motion patterns which have not accounted for individuality in the herd and instead assume a homogenized role for all members or sub-groups of the herd. Animal behavior experts have noted that domestic animals exhibit behaviors that are indicative of social hierarchy: leader/follower type behaviors are present as well as dominance and subordination, aggression and rank order, and specific social affiliations may also exist. Both wild and domestic cattle are social species, and group behaviors are likely to be influenced by the expression of specific social interactions. In this paper, Global Positioning System coordinate fixes gathered from a herd of beef cows tracked in open fields over several days at a time are utilized to learn a model that focuses on the interactions within the herd as well as its overall movement. Using these data in this way explores the validity of existing group behavior models against actual herding behaviors. Domain knowledge, location geography and human observations, are utilized to explain the causes of these deviations from this idealized behavior

Increasing condom use in heterosexual men: development of a theory-based interactive digital intervention

Increasing condom use to prevent sexually transmitted infections is a key public health goal. Interventions are more likely to be effective if they are theory- and evidence-based. The Behaviour Change Wheel (BCW) provides a framework for intervention development. To provide an example of how the BCW was used to develop an intervention to increase condom use in heterosexual men (the MenSS website), the steps of the BCW intervention development process were followed, incorporating evidence from the research literature and views of experts and the target population. Capability (e.g. knowledge) and motivation (e.g. beliefs about pleasure) were identified as important targets of the intervention. We devised ways to address each intervention target, including selecting interactive features and behaviour change techniques. The BCW provides a useful framework for integrating sources of evidence to inform intervention content and deciding which influences on behaviour to target

Detection of solvents using a distributed fibre optic sensor

A fibre optic sensor that is capable of distributed detection of liquid solvents is presented. Sensor interrogation using optical time domain reflectometry (OTDR) provides the capability of locating solvent spills to a precision of ±2 m over a total sensor length that may extend to 20 km

The development of Drink Less: an alcohol reduction smartphone app for excessive drinkers

Excessive alcohol consumption poses a serious problem for public health. Digital behavior change interventions have the potential to help users reduce their drinking. In accordance with Open Science principles, this paper describes the development of a smartphone app to help individuals who drink excessively to reduce their alcohol consumption. Following the UK Medical Research Council’s guidance and the Multiphase Optimization Strategy, development consisted of two phases: (i) selection of intervention components and (ii) design and development work to implement the chosen components into modules to be evaluated further for inclusion in the app. Phase 1 involved a scoping literature review, expert consensus study and content analysis of existing alcohol apps. Findings were integrated within a broad model of behavior change (Capability, Opportunity, Motivation-Behavior). Phase 2 involved a highly iterative process and used the “Person-Based” approach to promote engagement. From Phase 1, five intervention components were selected: (i) Normative Feedback, (ii) Cognitive Bias Re-training, (iii) Self-monitoring and Feedback, (iv) Action Planning, and (v) Identity Change. Phase 2 indicated that each of these components presented different challenges for implementation as app modules; all required multiple iterations and design changes to arrive at versions that would be suitable for inclusion in a subsequent evaluation study. The development of the Drink Less app involved a thorough process of component identification with a scoping literature review, expert consensus, and review of other apps. Translation of the components into app modules required a highly iterative process involving user testing and design modification

Effective Feedback to Improve Primary Care Prescribing Safety (EFIPPS) a pragmatic three-arm cluster randomised trial:designing the intervention (ClinicalTrials.gov registration NCT01602705)

Peer reviewedPublisher PD

Positioning system for wireless sensor networks with location fingerprinting

Wireless sensor networks (WSN) are networks that deploy hundreds or thousands of wireless sensors in a pre-defined area that can communicate with each other to detect, for example the ambient environment. Each sensor is composed of the four basic elements: transmitting unit, processing unit, power unit and sensing unit. The main task of each sensor is to detect events, perform a restricted set of local data processing tasks and then transmit the data. This technology still in its early stage new researches are being conducted intensively in MAC protocols, network and routing layer, and adaptation into various domains applications. In this proposal, the focus is placed to investigate algorithms in mapping the location of sensor nodes. Knowing the location of the sensor node is critically important; the knowledge of the location of the sensor node that reported a detected event can reduce the time for assistants reaching to the outbreak point. This can potentially save life or can bring the outbreak event under control in shortest time. As the sensor node's physical hardware is mainly comprises of low specification and low cost componentry to facilitate mass production hence affordable to be applied intensively in monitoring zone. This has created a tough challenge in mapping the locations of sensor nodes as the hard-ware can not provide precise timing in calculating time of flight of a packet which is an important parameter in estimating distance between transmitting node and receiving node. In general the sensor node is only equipped with a single antenna which has also rule out the possibility of using techniques rely on angle of arrival packet. Therefore, the research is limited to use the received signal strength as the main source in estimating the travelling distance for the received packet. This paper investigates positioning algorithms that based on received signal strength i.e., location fingerprinting. In positioning systems, location fingerprinting is also referred as pattern matching of radio signature. The advantages of using RF fingerprinting are it does not require any hardware modifications to the sensor node and in comparison to other algorithms it is immune environmental influences that caused signal attenuation such as multipath, fading, reflection, non line of sight, and etc. This paper focuses on challenges that relate specifically to the location mapping of wireless sensor node including radio propagation of low specification WSN hardware, accuracy, operational range and impact of environmental factors. The optimized positioning system for WSN is documented, and results gained from experiment based on IEEE 802.15.4 WSN platform is provided

Implementation of a herd management system with wireless sensor networks

This paper investigates an adaptation of Wireless Sensor Networks (WSNs) to cattle monitoring applications. The proposed solution facilitates the requirement for continuously assessing the condition of individual animals, aggregating and reporting this data to the farm manager. There are several existing approaches to achieving animal monitoring, ranging from using a store and forward mechanism to employing GSM-based techniques; these approaches only provide sporadic information and introduce a considerable cost in staffing and physical hardware. The core of this study is to overcome the aforementioned drawbacks by using alternative cheap, low power consumption sensor nodes capable of providing real-time communication at a reasonable hardware cost. In this paper, both the hardware and software has been designed to provide a solution which can obtain real-time data from dairy cattle whilst conforming to the limitations associated with WSNs implementations